CN111568398A - Physiological signal acquisition system based on body area network - Google Patents

Abstract

The invention provides a physiological signal acquisition system based on a body area network, comprising: a physiological signal acquisition device for collecting a user's physiological signal, and transmitting the collected physiological signal to an APP of an intelligent terminal through a Bluetooth communication technology; the APP, Used to receive and store physiological signals, and provide applications related to physiological signals. Among them, physiological signals include physiological signals representing emotional state, physiological signals representing physical state and number of steps; physiological signals representing emotional state include galvanic skin response signal and blood volume pulse signal, and physiological signals representing physical state include body temperature signal, heart rate signal Signal, blood pressure signal, blood oxygen signal and ECG signal; data interaction between the physiological signal acquisition device and the APP is carried out through the trusted acquisition mode. The present invention can detect the physical health state and emotional state of the user at the same time, so as to help the user to adjust his daily work and life in time and obtain a higher quality and healthier life.

Description

A Physiological Signal Acquisition System Based on Body Area Network

technical field

The invention relates to the technical field of intelligent services and trusted computing, in particular to a physiological signal acquisition system based on a body area network using bluetooth for data transmission.

Background technique

With the continuous development of network information technology and sensor technology, under the popularization of the Internet, more and more smart wearable products have been developed and gradually applied to people's daily life. Smart wearable products have become an important development direction in smart devices. Physiological sensor technology has begun to be widely used in the field of wearable devices. In the context of the "Internet +" era, a variety of smart wearable products have sprung up, including smart bracelets, smart watches, smart glasses, smart clothing, and more. These wearable devices all use physiological sensors, including heart rate sensors, pulse sensors, and body temperature sensors. In the future, with the development of technology and the increase of people's needs, wearable devices will further show a trend of diversification and high demand. Most of these smart wearable products collect physiological signals such as heart rate, blood oxygen, and even ECG. These physiological signals have certain symbolic meanings for the user's physical health status.

Smart wearable products are characterized by easy portability, intelligence, fine workmanship, and multi-functionality. At present, most smart wearable products have the function of detecting the user's physical health. Such as heart rate detection, calorie detection, etc. These physiological signal values are used to quantify the user's movement state and physical condition. Because it can detect the physical health of the user, it can play an important role in the health detection of sportsmen and the elderly. But now that products are becoming more and more intelligent, detecting the emotional state of users has also become an important thing. However, existing smart wearable products pay less attention to the detection of the user's emotional state.

GSR (Galvanic Skin Response, Galvanic Skin Response) and BVP (BloodVolume Pulse, blood volume pulse) are very important physiological signals that can express emotional state. The present invention is devoted to designing a system that can collect various physiological signals of the user. In addition to collecting body temperature, heart rate, blood pressure, blood oxygen and ECG, which can represent physical conditions, it also collects galvanic skin response GSR and blood volume pulse BVP that can represent emotional conditions, and calculates the user's steps through gyroscope data. The system adopts the combination of software and hardware, and uses Bluetooth for communication, which can realize the acquisition, storage and other applications of physiological signals, and has a trusted acquisition mode to deal with interference and external intrusion.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a physiological signal acquisition system based on a body area network, which can detect the physical health and emotional state of the user at the same time, so as to help the user to adjust his daily work and life in time, and obtain higher quality and a healthier life.

In order to solve the above-mentioned technical problems, the embodiments of the present invention provide the following solutions:

A body area network-based physiological signal acquisition system, comprising:

Physiological signal acquisition equipment, used to collect the user's physiological signals, and transmit the collected physiological signals to the APP of the smart terminal through Bluetooth communication technology;

The APP is used to receive and store the physiological signal, and provide applications related to the physiological signal.

Wherein, the physiological signals include physiological signals representing emotional states, physiological signals representing physical states, and steps; the physiological signals representing emotional states include galvanic skin response signals and blood volume pulse signals, and the physiological signals representing physical states The signals include body temperature signal, heart rate signal, blood pressure signal, blood oxygen signal and electrocardiogram signal; data interaction is performed between the physiological signal acquisition device and the APP through a trusted acquisition mode.

Preferably, the physiological signal collection device includes a wearable wristband, elbow pads and ankle pads; the wristband is used for collecting galvanic skin response signals and blood volume pulse signals, and the elbow pads are used for collecting body temperature signals, heart rate signals signal, blood pressure signal, blood oxygen signal and electrocardiogram signal, the ankle brace is used to collect the number of steps.

Preferably, the wristband includes a first microcontroller, a first sensor group, a first memory, a first Bluetooth module, a first power supply, a first hardware security module, and an LCD respectively connected to the first microcontroller. Display screen, and supporting peripheral circuits;

The first sensor group is used to collect galvanic skin response signals and blood volume pulse signals;

the first memory is used for storing data collected by the first sensor group;

The first Bluetooth module is used to transmit the collected data to the APP through Bluetooth communication technology;

the first power source is used for powering the wristband;

The LCD display screen is used to display the collected data;

The first hardware security module is used to ensure data transmission security;

The first microcontroller is used to control the first sensor group, the first memory, the first Bluetooth module, the first power supply, the first hardware security module and the LCD display screen to work .

Preferably, the elbow pad includes a second microcontroller, a second sensor group, a second memory, a second Bluetooth module, a second power supply, a second hardware security module respectively connected to the second microcontroller, and supporting peripheral circuits;

The second sensor group is used for collecting body temperature signal, heart rate signal, blood pressure signal, blood oxygen signal and electrocardiogram signal;

the second memory is used for storing the data collected by the second sensor group;

The second bluetooth module is used to transmit the collected data to the APP through bluetooth communication technology;

the second power source is used for powering the elbow pad;

The second hardware security module is used to ensure data transmission security;

The second microcontroller is used to control the second sensor group, the second memory, the second Bluetooth module, the second power supply, and the second hardware security module to work.

Preferably, the ankle brace includes a third microcontroller, a gyroscope, a third memory, a third Bluetooth module, a third power supply, a third hardware security module connected to the third microcontroller, and a matching Peripheral circuits;

The gyroscope is used to collect steps;

The third memory is used to store the data collected by the gyroscope;

The third Bluetooth module is used to transmit the collected data to the APP through Bluetooth communication technology;

the third power source is used for powering the ankle brace;

The third hardware security module is used to ensure data transmission security;

The third microcontroller is used to control the gyroscope, the third memory, the third Bluetooth module, the third power supply, and the third hardware security module to work.

Preferably, the APP includes:

a data receiving unit for receiving data in the collected physiological signals;

a data storage unit for storing data in the collected physiological signals;

The data viewing unit is used to provide the data in the stored physiological signals to the user for analysis and viewing;

a data exporting unit for exporting the data in the stored physiological signal;

a time calibration unit, configured to obtain the latest time through the Internet, and then transmit it to the physiological signal acquisition device through the Bluetooth communication technology, so that the physiological signal acquisition device updates the time value;

The trusted acquisition unit is used for encryption and decryption during communication and intrusion detection to ensure the security of data transmission.

The data in the stored physiological signals include: acquisition time, galvanic skin response signal value, blood volume pulse signal value, body temperature signal value, heart rate signal value, blood pressure signal value, blood oxygen signal value, ECG signal value, step value .

Preferably, the trusted collection mode includes:

For the physiological signal acquisition device, a hardware security module is used to protect the data security of the hardware;

For the APP, the key technology is used to protect the data security of the software, and the machine learning technology is used to design a model for intrusion detection to defend against external intrusions.

Preferably, the hardware security module includes a fourth microcontroller, a fourth memory, a switch, and a supporting peripheral circuit respectively connected to the fourth microcontroller;

the fourth memory is used to record logs;

The switch is used to be responsible for the switch of the trusted collection mode and the hardware reset after abnormality is detected;

The fourth microcontroller is used to control the fourth memory and the switch to work.

Preferably, the trusted collection mode of the APP includes:

The robot learning communication security unit is used to design an intrusion detection model using machine learning technology, and encrypts and decrypts communication by using three key algorithms and an additional data group;

The intrusion detection unit is used for the intrusion detection model designed by machine learning technology, using support vector machine, decomposition machine and convolutional neural network algorithm for model training, and compares the accuracy index, and selects the appropriate index by comprehensively considering various accuracy index. The model is deployed into the APP for real-time intrusion detection.

The above-mentioned scheme of the present invention at least includes the following beneficial effects:

1) There are mainly two types of physiological signals collected by the system of the present invention, and the user's emotional state and physical state can be well detected by these two types of physiological signals. The first category is physiological signals representing emotional states, including galvanic skin response (GSR) signals and blood volume pulse (BVP) signals. These two physiological signals do not represent the physical state, but reflect the psychological emotional state to a certain extent. For example, according to the characteristics of the GSR signal, the system using the GSR signal can reflect the user's emotional fluctuations in real time. When the user is excited, the user's GSR value will be higher than that in the calm state. The more excited the user is, the higher the GSR value increases. Conversely, when users are depressed, their GSR value will be lower. The system collects these two physiological signals and generates a data set, which provides suitable materials for further analysis. The second category is the five physiological signals that represent the state of the body, namely body temperature, heart rate, blood oxygen, blood oxygen and electrocardiogram. Through these five signals, the user's physical health status can be detected from various angles. For example, blood oxygen is an important physiological parameter of human respiratory and circulatory functions; blood pressure is a very important physiological signal, and cardiovascular and cerebrovascular diseases can be prevented by detecting blood pressure.

2) The system of the present invention adopts the Bluetooth communication technology to realize the combination of software and hardware. The data storage function is mainly realized by the APP, so that the hardware part does not have to be limited by the storage capacity of the memory chip. Since smartphones generally have Bluetooth communication functions, if communication technologies such as Zigbee are used, the mobile phone cannot directly receive data from the wristband. In the case of using Bluetooth communication, after the user has the wristband, elbow pads and ankle pads in the system, the APP of the system can be installed on the smartphone.

3) The system of the present invention has a selectable credible collection mode. In daily life, there are usually various communication networks around people's communication equipment, and there is a danger of being invaded in a complex network environment. The system can deal with external intrusions and protect hardware devices and APPs through the trusted acquisition mode. Through the trusted acquisition mode, the system can provide users with more effective security protection, which not only protects important personal privacy data, but also better guarantees the availability of the system and enhances the credibility of the physiological signal acquisition system.

Description of drawings

1 is a schematic structural diagram of a body area network-based physiological signal acquisition system provided by an embodiment of the present invention;

2 is a schematic structural diagram of a wristband in an embodiment of the present invention;

Fig. 3 is the structural representation of the elbow pad in the embodiment of the present invention;

Fig. 4 is the structural representation of the ankle brace in the embodiment of the present invention;

5 is a schematic structural diagram of an APP in an embodiment of the present invention;

6 is a schematic structural diagram of a hardware security module in an embodiment of the present invention;

7 is a schematic diagram of the workflow of a group of data from collection to storage to application in an embodiment of the present invention;

FIG. 8 is a schematic diagram of the main functions of the wristband in the embodiment of the present invention.

Description of reference numerals: 1-physiological signal acquisition device; 2-APP; 3-wristband; 4-elbow pad; 5-ankle pad; 201-data receiving unit; 202-data storage unit; 203-data viewing unit; 204 - data derivation unit; 205 - time calibration unit; 206 - trusted acquisition unit; 301 - first microcontroller; 302 - first sensor group; 303 - first memory; 304 - first Bluetooth module; 305 - first 306-first hardware security module; 307-LCD display screen; 401-second microcontroller; 402-second sensor group; 403-second memory; 404-second Bluetooth module; 405-second power supply; 406-second hardware security module; 501-third microcontroller; 502-gyroscope; 503-third memory; 504-third Bluetooth module; 505-third power supply; 506-third hardware security module; 601- The fourth microcontroller; 602 - the fourth memory; 603 - the switch.

Detailed ways

In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

An embodiment of the present invention provides a system for collecting physiological signals based on a body area network. As shown in FIG. 1 , the system for collecting physiological signals includes:

The physiological signal acquisition device 1 is used to collect the physiological signals of the user, and transmit the collected physiological signals to the APP2 of the smart terminal through the Bluetooth communication technology;

APP2, for receiving and storing the physiological signal, and providing applications related to the physiological signal.

Wherein, the physiological signals include physiological signals representing emotional states, physiological signals representing physical states, and steps; the physiological signals representing emotional states include galvanic skin response signals and blood volume pulse signals, and the physiological signals representing physical states The signals include body temperature signal, heart rate signal, blood pressure signal, blood oxygen signal and electrocardiogram signal; data interaction is performed between the physiological signal acquisition device and the APP through a trusted acquisition mode.

Among them, the trusted collection mode can ensure reliable data collection in complex environments, and enabling the trusted collection mode can deal with intrusion attacks on hardware and software, and ensure the reliability and security of the system.

There are mainly two types of physiological signals collected by the system of the present invention, and the user's emotional state and physical state can be well detected by the two types of physiological signals. The first category is physiological signals representing emotional states, including galvanic skin response (GSR) signals and blood volume pulse (BVP) signals. These two physiological signals do not represent the physical state, but reflect the psychological emotional state to a certain extent. For example, according to the characteristics of the GSR signal, the system using the GSR signal can reflect the user's emotional fluctuations in real time. When the user is excited, the user's GSR value will be higher than that in the calm state. The more excited the user is, the higher the GSR value increases. Conversely, when users are depressed, their GSR value will be lower. The system collects these two physiological signals and generates a data set, which provides suitable materials for further analysis. The second category is the five physiological signals that represent the state of the body, namely body temperature, heart rate, blood oxygen, blood oxygen and electrocardiogram. Through these five signals, the user's physical health status can be detected from various angles. For example, blood oxygen is an important physiological parameter of human respiratory and circulatory functions; blood pressure is a very important physiological signal, and cardiovascular and cerebrovascular diseases can be prevented by detecting blood pressure.

The system of the present invention adopts the bluetooth communication technology to realize the combination of software and hardware. The data storage function is mainly realized by the APP, so that the hardware part does not have to be limited by the storage capacity of the memory chip. Since the smart phone generally has the Bluetooth communication function, in the case of using the Bluetooth communication, the APP of the system can be conveniently used by installing the APP on the smart phone.

The system of the present invention has a selectable credible collection mode. In daily life, there are usually various communication networks around people's communication equipment, and there is a danger of being invaded in a complex network environment. The system can deal with external intrusions and protect hardware devices and APPs through the trusted acquisition mode. Through the trusted acquisition mode, the system can provide users with more effective security protection, which not only protects important personal privacy data, but also better guarantees the availability of the system and enhances the credibility of the physiological signal acquisition system.

Further, the physiological signal acquisition device 1 includes wearable wristbands, elbow pads and ankle pads; the wristbands are used to collect galvanic skin response signals and blood volume pulse signals, and the elbow pads are used to collect body temperature signals, heart rate signals, blood pressure signals, Blood oxygen signal and ECG signal, ankle braces are used to collect steps.

The physiological signal acquisition system proposed by the present invention is composed of wearable wristbands, elbow pads, ankle pads, and smart phones to form a body area network. Among them, the wristband is used to collect physiological signals that can represent emotional states; the elbow pads are used to collect physiological signals that can represent the physical state; the ankle pads are used to calculate the number of steps of the user; and the data of these physiological signals are transmitted to the In the APP in the smart phone; and store these data and other applications; design a trusted collection mode to ensure the security of the data. The credible collection mode of the present invention is optional, and can safely collect various physiological signals in the presence of external interference or potential safety hazards. Through the collected signals, some changes in emotional state and changes in physical state can be initially observed.

Further, as shown in FIG. 2 , the wristband 3 includes a first microcontroller 301 , a first sensor group 302 , a first memory 303 , a first Bluetooth module 304 , and a first power supply respectively connected to the first microcontroller 301 . 305. The first hardware security module 306, the LCD display screen 307, and the supporting peripheral circuits;

The first sensor group 302 is used for collecting galvanic skin response signals and blood volume pulse signals;

The first memory 303 is used to store the data collected by the first sensor group 302;

The first Bluetooth module 304 is used to transmit the collected data to the APP2 through the Bluetooth communication technology;

The first power source 305 is used to supply power to the wristband 3;

The LCD display screen 307 is used to display the collected data;

The first hardware security module 306 is used to ensure data transmission security;

The first microcontroller 301 is used to control the first sensor group 302 , the first memory 303 , the first Bluetooth module 304 , the first power supply 305 , the first hardware security module 306 and the LCD display screen 307 to work.

The wristband 3 adopts a rigid shell, and the first sensor group 302 includes a GSR module and a BVP module; the GSR module is used to collect GSR physiological signals, and is connected to the first microcontroller 301 by an ADC; the BVP module is used to collect BVP physiological signals, The ADC is used to connect with the first microcontroller 301 .

The first power source 305 is a rechargeable battery, which provides the electrical energy required for the operation of the entire wristband; the first memory 303 is a module for temporarily storing physiological signals in the wristband, and a Flash memory can be selected, which can be stored for a long time in the event of a power failure The data is non-volatile and can more reliably store the collected physiological signal data.

The LCD display 307 is the display part of the wristband, and works together with the miniature buttons; the first Bluetooth module 304 is responsible for transmitting the physiological signal data in the Flash memory in the wristband to the APP of the smartphone, and the selected Bluetooth module should use Bluetooth 4 Modules above version; peripheral circuits include wires, resistors, and micro buttons.

The first hardware security module 306 is an important part for performing trusted collection, and this module is mainly responsible for ensuring the data security of the hardware part.

The first microcontroller 301 is the control part of the entire wristband, and can use the STM32F103ZET6 chip, but is not limited to this chip. The first microcontroller 301 is the core of the embedded device and must have sufficient performance to support the operation of other modules. In terms of interface type and quantity, the selected microcontroller should have more than two ADC channels and enough I/O ports to control other modules.

Further, as shown in FIG. 3 , the elbow pad 4 includes a second microcontroller 401 , a second sensor group 402 , a second memory 403 , a second Bluetooth module 404 , and a second power supply respectively connected to the second microcontroller 401 . 405, a second hardware security module 406, and supporting peripheral circuits;

The second sensor group 402 is used for collecting body temperature signal, heart rate signal, blood pressure signal, blood oxygen signal and electrocardiogram signal;

The second memory 403 is used to store the data collected by the second sensor group 402;

The second Bluetooth module 404 is used to transmit the collected data to APP2 through the Bluetooth communication technology;

The second power source 405 is used to supply power to the elbow pad 4;

The second hardware security module 406 is used to ensure data transmission security;

The second microcontroller 401 is used to control the second sensor group 402 , the second memory 403 , the second Bluetooth module 404 , the second power supply 405 , and the second hardware security module 406 to work.

The elbow pads 4 are made of flexible materials, and the second sensor group 402 includes a body temperature sensor, a heart rate sensor, a blood pressure sensor, a blood oxygen sensor, and an electrocardiogram sensor, which are used to collect body temperature signals, heart rate signals, blood pressure signals, and blood oxygen sensors, respectively. Signals and ECG Signals.

The second power source 405 is a rechargeable battery, which provides the electric energy required for the operation of the entire elbow pad; the second memory 403 is a module for temporarily storing physiological signals in the elbow pad, and a Flash memory can be selected, which can be stored for a long time in the event of a power failure The data is non-volatile and can more reliably store the collected physiological signal data.

The second Bluetooth module 404 is responsible for transmitting the physiological signal data in the flash memory in the elbow pad to the APP of the smart phone. The selected Bluetooth module should be a module with a Bluetooth 4 version or above; the peripheral circuit includes wires, resistors, and miniature buttons.

The second hardware security module 406 is an important part for performing trusted collection, and this module is mainly responsible for ensuring the data security of the hardware part.

The second microcontroller 401 is the control part of the entire elbow pad, and can use the STM32F103ZET6 chip, but is not limited to this chip. The second microcontroller 401 is the core of the embedded device and must have sufficient performance to support the operation of other modules. In terms of interface type and quantity, the selected microcontroller should have more than two ADC channels and enough I/O ports to control other modules.

Further, as shown in FIG. 4 , the ankle brace 5 includes a third microcontroller 501, a gyroscope 502, a third memory 503, a third Bluetooth module 504, a third power supply 505, The third hardware security module 506, and supporting peripheral circuits;

The gyroscope 502 is used to collect steps;

The third memory 503 is used to store the data collected by the gyroscope 502;

The third Bluetooth module 504 is used to transmit the collected data to APP2 through the Bluetooth communication technology;

The third power source 505 is used for powering the ankle brace 5;

The third hardware security module 506 is used to ensure data transmission security;

The third microcontroller 501 is used to control the gyroscope 502 , the third memory 503 , the third Bluetooth module 504 , the third power supply 505 , and the third hardware security module 506 to work.

The ankle brace 5 is made of a shell made of a flexible material, and the gyroscope 502 collects information such as the angle of the user's calf to provide a basis for calculating the number of steps.

The third power source 505 is a rechargeable battery, which provides the electrical energy required for the operation of the entire ankle brace; the third memory 503 is a module for temporarily storing physiological signals in the ankle brace, and a Flash memory can be selected, which can be stored for a long time in the event of a power failure The data is non-volatile and can more reliably store the collected physiological signal data.

The third Bluetooth module 504 is responsible for transmitting the physiological signal data in the Flash memory in the ankle brace to the APP of the smartphone. The selected Bluetooth module should be a module with a version of Bluetooth 4 or higher; the peripheral circuit includes wires, resistors, and miniature buttons.

The third hardware security module 506 is an important part for performing trusted collection, and this module is mainly responsible for ensuring the data security of the hardware part.

The third microcontroller 501 is the control part of the entire ankle brace, and can use the STM32F103ZET6 chip, but is not limited to this chip. The third microcontroller 501 is the core of the embedded device and must have sufficient performance to support the operation of other modules. In terms of interface type and quantity, the selected microcontroller should have more than two ADC channels and enough I/O ports to control other modules.

The wristband part is made of hard material, such as plastic or metal. Since the elbow pads and ankle pads need to have the function of protecting the body, the outside of the acquisition circuit needs to be made of flexible materials, so that the user can wear them comfortably. In the elbow and ankle support sections, the various devices are selected to be as small as possible. When the acquisition circuit is rigid, a non-conductive flexible material such as polyurethane is used to make the casing, and then the acquisition device with the flexible casing is integrated into the wrist or ankle brace, so as to make the wrist and ankle brace as comfortable to wear as possible.

Due to the popularity of smart phones, smart phones generally have a Bluetooth communication module. Only by installing the APP of this system on the smart phone, you can receive data from the wristband, elbow pads, and ankle pads through Bluetooth, and store and store the data. View and other operations.

Further, as shown in Figure 5, the APP includes:

a data receiving unit 201, configured to receive data in the collected physiological signals;

a data storage unit 202, configured to store data in the collected physiological signals;

A data viewing unit 203, configured to provide the data in the stored physiological signals to the user for analysis and viewing;

a data deriving unit 204, for deriving the data in the stored physiological signal;

a time calibration unit 205, configured to obtain the latest time through the Internet, and then transmit it to the physiological signal acquisition device through the Bluetooth communication technology, so that the physiological signal acquisition device updates the time value;

The trusted collection unit 206 is used for encryption and decryption during communication, and for intrusion detection, so as to ensure the security of data transmission.

The data in the stored physiological signals include: acquisition time, galvanic skin response (GSR) signal value, blood volume pulse (BVP) signal value, body temperature signal value, heart rate signal value, blood pressure signal value, blood oxygen signal value, cardiac Electrical signal value, step value.

Specifically, the database of the data storage unit 202 in the APP software of the system adopts the SQLite database. Using APP for data storage, data storage and other work can be concentrated in the software of the smartphone, and the hardware part focuses on signal acquisition. At the same time, the amount of data that can be stored is not limited by the storage capacity of wearable devices such as wristbands.

The data checking unit 203 is that the user can perform certain analysis and checking on the stored physiological signal data. This function can not only find physiological signal data by time, but also visualize various physiological signal data after preliminary analysis. For example, the GSR signal value can be visualized through a graph to make the change of the user's emotional state more intuitive.

For example, the system can perform preliminary analysis on the GSR signal value and the BVP signal value, including but not limited to the following analysis methods:

1) Analyze the user's GSR value in a calm state.

2) Analyze the state of the GSR signal value at each moment relative to the GSR value in the calm state.

3) For the BVP signal, other physiological signals, such as heart rate, can be calculated by an algorithm.

4) According to the signal acquisition time and its value, draw the physiological signal curve.

The system can also have a preliminary analysis of the signal values such as body temperature and heart rate. For example, for the ECG signal, the ECG signal is collected at an appropriate frequency and displayed in the form of an ECG.

The user can view the stored data according to the time, the physiological signal curve, and the results after the preliminary analysis of the system.

The data exporting unit 204 can export the physiological signal data stored in the database into file formats such as xlsx or csv. Then according to specific needs, the data file is copied out. These data files can provide datasets for technologies such as affective computing for further analysis.

The time calibration unit 205 is embodied in that the APP obtains the latest time through the Internet, and then transmits it to the physiological signal acquisition device through Bluetooth, so that the physiological signal acquisition device updates the time value. The time is updated once a day to eliminate timing errors that may be introduced by physiological signal acquisition equipment.

The trusted collection unit 206 includes encryption and decryption when establishing communication, feature extraction and intrusion detection of the software running state when the software is running. This function is optional, and the hardware security module must be turned on before this function can be used.

Further, the trusted collection mode includes:

For the physiological signal acquisition equipment, the hardware security module is used to protect the data security of the hardware;

For the APP, the key technology is used to protect the data security of the software, and the machine learning technology is used to design a model for intrusion detection to prevent external intrusions.

The trusted acquisition mode can enhance the reliability and security of the system through these methods. In the trusted collection mode, the security of the hardware and the security of the APP are mainly guaranteed. In order to enhance the credibility of the whole acquisition system, according to the realization form of the acquisition part using hardware and software, the trusted acquisition mode also detects and protects these two parts respectively. The trusted acquisition mode in the system is an optional mode, that is, in the case of external security risks, this mode can be turned on for data acquisition of physiological signals.

Further, as shown in FIG. 6 , the hardware security module includes a fourth microcontroller 601, a fourth memory 602 connected to the fourth microcontroller 601, a switch 603, and a supporting peripheral circuit;

The fourth memory 602 is used to record logs;

The switch 603 is used to be responsible for the switch of the trusted collection mode and the hardware reset after abnormality is detected;

The fourth microcontroller 601 is used to control the fourth memory 602 and the switch 603 to work.

It should be noted that the first hardware security module 306 in the wristband, the second hardware security module 406 in the elbow pad, and the third hardware security module 506 in the ankle pad can all adopt the structure of the above-mentioned hardware security module.

In the application process, a short press of the switch 603 can turn on and off the trusted acquisition mode, and a long press for 5 seconds can stop the hardware device from collecting physiological signals and Bluetooth communication when the hardware device faces security problems. After the communication is terminated due to security issues, it is necessary to re-establish communication with the original paired device (ie, the smartphone). If the communication is terminated twice due to security issues in a short period of time, the hardware security module will send an instruction to let the acquisition part specify the physiological signal data in the memory chip and the current Bluetooth pairing information. The hardware security module can perform communication authentication and also send control commands to clear and collect some physiological data. By using the interrupt priority, after the trusted acquisition mode is turned on, the instruction sent by the hardware security module to each microcontroller has the highest priority. By using the interrupt priority method, it is ensured that the acquisition device can be reset when it encounters a security problem, so as to ensure the security of the acquisition device.

At regular intervals, the hardware security module obtains the current communication information and verifies the identity of the other party of the communication. When an abnormality is found, the hardware security module calculates whether to stop sending the physiological signal data.

The opening and closing of the hardware security module is only controlled by the switch of this module. In the case that the acquisition device Bluetooth has been paired, the hardware security module should prevent other communications, that is, when the acquisition device has been paired, the acquisition device only communicates with the current communication device and does not accept communication requests from other devices.

Further, the trusted collection mode of the APP includes:

The robot learning communication security unit is used to design an intrusion detection model using machine learning technology, and encrypts and decrypts communication by using three key algorithms and an additional data group;

The intrusion detection unit is used for intrusion detection models designed by machine learning technology, using algorithms such as support vector machines, decomposition machines, and convolutional neural networks for model training, and comparing the accuracy indicators. Appropriate models are deployed into the APP for real-time intrusion detection.

In the present invention, the encryption and decryption of the hardware security module and the APP use a symmetric encryption algorithm. The hardware security module and the APP store three encryption algorithms, which are AES, DES and 3DES. When the hardware security module is turned on, the information that the hardware security module has been turned on is sent to the APP through the collection device. Only after receiving the information that the hardware security module has been turned on, the APP will initiate encryption and decryption communication with the hardware device. When the hardware security module is turned off, the communication about encryption and decryption initiated by the APP will be regarded as invalid information by the hardware device.

AES uses a 128-bit key, DES uses a 56-bit key, and 3DES uses a 112-bit key. Each time the hardware security module is turned on, in addition to the information contained in encryption and decryption, it also includes a 5-bit data segment. The first and second digits represent the hardware device number that initiates the communication, where the wristband number is 00, the elbow pad number is 01, and the ankle pad number is 10. The third and fourth digits represent the key algorithm used for this encryption and decryption communication. 00 means using AES algorithm, 01 means using DES algorithm, 10 means using 3DES algorithm. Because the number of key bits used by the three algorithms is different. The 5th bit of the data segment is used to solve this problem. The 0 on the 5th bit represents the number of bits required for the algorithm to be taken forward from the 1st bit in the keys stored in the hardware and APP. A 1 on bit 5 indicates the number of bits required for the algorithm to be reversed from bit 128 in the keys stored in hardware and APP. For example: the data segment is 01100, which means that the encryption and decryption calculation initiated by the elbow pad is calculated by using the DES algorithm, and the 56-bit data from the first bit in the original key is taken forward as the key of the DES algorithm; this data The segment is 10011, which means that the encryption and decryption calculations initiated by the ankle brace are calculated using the 3DES algorithm, and the 112-bit data from the 128th bit in the original key is reversed as the key of the 3DES algorithm. Cryptographic computations only take place when the hardware security module is turned on to ensure that the device that is about to communicate is authentic. The hardware security module should also record security logs and send abnormal warnings to the mobile phone.

There is a lot of software today that uses signature-based methods to identify security threats. Signature-based approaches involve generating a unique signature for each previously known malware, while detection involves scanning the application to match existing signatures in the malware database. There are also heuristic-based methods that rely on explicit differentiation rules to differentiate malware, leading to errors caused by human bias. In fact, neither approach will work if the development of malware databases or differentiation rules cannot keep up with the emergence and development of new malware.

To overcome the above two problems, machine learning-based intrusion detection techniques can be used. Machine learning-based intrusion detection techniques uncover previously undetected malicious samples.

Existing machine learning techniques for intrusion detection yield high false positive rates and limited accuracy. This may be due to the use of simpler models such as first-order models or linear classifiers. These models are not very effective when dealing with more feature dimensions and nonlinear relationships. Considering the interactions and potential relationships between features, it is necessary to introduce nonlinearity into intrusion detection. For example, an app requesting both GPS and SEND_SMS permissions may be attempting to perform location leaks, and the presence of just one of these requests does not indicate any malicious behavior. And the request for GPS location may also be in preparation for turning on Bluetooth and Wi-Fi.

In order to protect the data security of users and the security of the acquisition system, it is necessary to protect the APP part. This system uses algorithms such as support vector machines, decomposition machines and convolutional neural networks in machine learning techniques for model training, and these models can handle nonlinear situations.

To evaluate performance, metrics used include accuracy, false positive rate, recall rate, F1 score, AUC, ROC. Taking these metrics into consideration, choose the most appropriate model for deployment. The system deploys the trained model to the smartphone, extracts the features required for detection by the APP, and performs intrusion detection for the APP. When the APP is running normally, the extracted features do not need to be stored for too long. When an APP may face a security problem, the APP records various characteristics of the situation. The features extracted during detection can provide data for further improving the performance of intrusion detection.

FIG. 7 is a schematic diagram of the workflow of a group of data from collection to storage and then to application in an embodiment of the present invention. Starting from the acquisition of physiological signal data through the corresponding sensor, the physiological signal data is stored in the flash memory of the wristband, and then transmitted to the APP of the smartphone through Bluetooth communication, and the physiological signal data is then stored in the database SQLite. Usually, a set of data is a necessary process from collecting to being stored in the APP. Then, according to the user's needs, it is judged whether there is a control instruction input. If not, the data storage is completed once. If there is a control command input, then determine what type of control command it is, and then provide corresponding functions according to the type of control command.

Taking the wristband as an example, FIG. 8 is a schematic diagram of the main functions of the wristband in the embodiment of the present invention. LCD display and key input realize input and output functions, system control provides function configuration and time calibration for the wristband, data acquisition, data storage and Bluetooth communication are related functions to collect and store physiological signals. The functions of the elbow pads and ankle pads are roughly the same as those shown in Figure 8. The difference is that the elbow pads and ankle pads do not have an LCD display function, which will not be repeated here.

The above are the preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, without departing from the principles of the present invention, several improvements and modifications can be made. These improvements and modifications It should also be regarded as the protection scope of the present invention.

Claims (9)

1. a physiological signal acquisition system based on body area network, is characterized in that, comprises: Physiological signal acquisition equipment, used to collect the user's physiological signals, and transmit the collected physiological signals to the APP of the smart terminal through Bluetooth communication technology; The APP is used to receive and store the physiological signal, and provide applications related to the physiological signal. Wherein, the physiological signals include physiological signals representing emotional states, physiological signals representing physical states, and steps; the physiological signals representing emotional states include galvanic skin response signals and blood volume pulse signals, and the physiological signals representing physical states The signals include body temperature signal, heart rate signal, blood pressure signal, blood oxygen signal and electrocardiogram signal; data interaction is performed between the physiological signal acquisition device and the APP through a trusted acquisition mode. 2 . The physiological signal collection system according to claim 1 , wherein the physiological signal collection device comprises wearable wristbands, elbow pads and ankle pads; the wristbands are used to collect galvanic skin response signals and blood. 3 . Volume pulse signal, the elbow brace is used to collect body temperature signal, heart rate signal, blood pressure signal, blood oxygen signal and electrocardiogram signal, and the ankle brace is used to collect the number of steps. 3 . The physiological signal acquisition system according to claim 2 , wherein the wristband comprises a first microcontroller, a first sensor group, a first memory, a first sensor group, a first memory, a first a Bluetooth module, a first power supply, a first hardware security module, an LCD display screen, and a supporting peripheral circuit; The first sensor group is used to collect galvanic skin response signals and blood volume pulse signals; the first memory is used for storing data collected by the first sensor group; The first Bluetooth module is used to transmit the collected data to the APP through Bluetooth communication technology; the first power source is used for powering the wristband; The LCD display screen is used to display the collected data; The first hardware security module is used to ensure data transmission security; The first microcontroller is used to control the first sensor group, the first memory, the first Bluetooth module, the first power supply, the first hardware security module and the LCD display screen to work . 4 . The physiological signal acquisition system according to claim 2 , wherein the elbow pad comprises a second microcontroller, a second sensor group, a second memory, a second sensor group, a second memory, a first Two Bluetooth modules, a second power supply, a second hardware security module, and supporting peripheral circuits; The second sensor group is used for collecting body temperature signal, heart rate signal, blood pressure signal, blood oxygen signal and electrocardiogram signal; the second memory is used for storing the data collected by the second sensor group; The second bluetooth module is used to transmit the collected data to the APP through bluetooth communication technology; the second power source is used for powering the elbow pad; The second hardware security module is used to ensure data transmission security; The second microcontroller is used to control the second sensor group, the second memory, the second Bluetooth module, the second power supply, and the second hardware security module to work. 5 . The physiological signal acquisition system according to claim 2 , wherein the ankle brace comprises a third microcontroller, a gyroscope, a third memory, a third bluetooth connected to the third microcontroller respectively. 6 . module, third power supply, third hardware security module, and supporting peripheral circuits; The gyroscope is used to collect steps; The third memory is used to store the data collected by the gyroscope; The third Bluetooth module is used to transmit the collected data to the APP through Bluetooth communication technology; the third power source is used for powering the ankle brace; The third hardware security module is used to ensure data transmission security; The third microcontroller is used to control the gyroscope, the third memory, the third Bluetooth module, the third power supply, and the third hardware security module to work. 6. The physiological signal acquisition system according to claim 1, wherein the APP comprises: a data receiving unit for receiving data in the collected physiological signals; a data storage unit for storing data in the collected physiological signals; The data viewing unit is used to provide the data in the stored physiological signals to the user for analysis and viewing; a data exporting unit for exporting the data in the stored physiological signal; a time calibration unit, configured to obtain the latest time through the Internet, and then transmit it to the physiological signal acquisition device through the Bluetooth communication technology, so that the physiological signal acquisition device updates the time value; The trusted acquisition unit is used for encryption and decryption during communication and intrusion detection to ensure the security of data transmission. The data in the stored physiological signals include: acquisition time, galvanic skin response signal value, blood volume pulse signal value, body temperature signal value, heart rate signal value, blood pressure signal value, blood oxygen signal value, ECG signal value, step value . 7. The physiological signal acquisition system according to claim 1, wherein the credible acquisition mode comprises: For the physiological signal acquisition device, a hardware security module is used to protect the data security of the hardware; For the APP, the key technology is used to protect the data security of the software, and the machine learning technology is used to design a model for intrusion detection to defend against external intrusions. 8 . The physiological signal acquisition system according to claim 7 , wherein the hardware security module comprises a fourth microcontroller, a fourth memory connected to the fourth microcontroller, a switch, and a matching device. 9 . Peripheral circuits; the fourth memory is used to record logs; The switch is used to be responsible for the switch of the trusted collection mode and the hardware reset after abnormality is detected; The fourth microcontroller is used to control the fourth memory and the switch to work. 9. The physiological signal acquisition system according to claim 7, wherein the credible acquisition mode of the APP comprises: The robot learning communication security unit is used to design an intrusion detection model using machine learning technology, and encrypts and decrypts communication by using three key algorithms and an additional data group; The intrusion detection unit is used for the intrusion detection model designed by machine learning technology, using support vector machine, decomposition machine and convolutional neural network algorithm for model training, and compares the accuracy index, and selects the appropriate index by comprehensively considering various accuracy index. The model is deployed into the APP for real-time intrusion detection.

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